ASSIGNMENT

 

Table of Contents

Task 1. 3

Task 2. 4

Task 3. 5

Task 4. 5

Task 5. 7

Task 6. 9

Task 7. 10

Task 8. 11

Task 9. 12

Task 10. 13

Task 11. 15

Task 12. 17

Task 13. 19

Task 14. 21

Task 15. 23

Task 16. 25

Reference List 28

 

 

 

 

This particular assessment is based on the visualization of authentic engineering datasets, to analyze telemetry gathering of data from an authentic Formula One Grand Prix race and also different properties of that same (Waskom 2021.). The whole task is performed on the Python Jupyter Notebook platform and the entire work is performed in sixteen different stages, all of which are described below.

Figure 1: Import of necessary libraries

In this assessment to perform the enatir work different types of Python libraries are imported, such as pandas, numpy and many more, the above figure shows the same.

 

Task 1

Figure 2: Visualization of CSV data set

 

Task 1 is based on the importance of The CSV data set, In this task, a Dutch2022. CSV dataset is used and the above figure shows the importation of that same.

 

Task 2

 

 

 

Figure 3: Displays data description

 

Task 2 is the description of the conversion of time delts to create a new column that may be shown in the lap time in seconds (Yang 2022).

Task 3

Figure 4: Visualization of null values

Task 3 describes the determination of those time laps that are normal. Therefore, the above figure shows the shape of the CSV data set.

 

 

Task 4

 

Figure 5: Coding to show normal lap times for the driver

The above figure shows the coding visualization to display normal lap times for the driver VER. Through a data frame creation, task 4 has been created.

 

 

Figure 6: Plot visualization of normal lap times for the driver

The above plot is a line plot visualization to display normal lap time for the driver. Therefore, in this plot, the X-axis holds lap time in seconds and the Y-axis holds lap number.

 

Task 5

 

 

Figure 7: Coding to show the total number of laps reached on each tyre compound

The above figure is the coding visualization, to plot a pie chart to show the total number of laps raced on each tyre compound.

Figure 8: Pie chart for the total number of laps reached on each tyre compound

Therefore, implement a pie chart to show different tyre compounds, in terms of hard, medium, and soft, the above figure is displayed.

Task 6

 

Figure 9: Coding for the fastest lap time for each driver

Task 6 is based on the implementation to show the fastest lap time for each driver in the considered data set.

Figure 10: Plot to visualize the fastest lap time for each driver

The above figure is a count plot to visualize task 6, which means it shows the count plot to show the values of lap time and drivers.

 

Task 7

 

 

 

Figure 11: Coding for the fastest lap time for each driver as a box plot

The above figure shows the coding visualization to represent the fastest lap time for each driver.

 

 

Figure 12: Box plot to visualize the fastest lap time for each driver

 

The above figure represents a box plot to show the visualization of the fastest lap time for each driver and task 7 is based on that same (Sievert 2020.).

 

 

Task 8

 

 

Figure 13:Visualization of tyre compound used in each stint for each driver

The above figure is the coding visualization to represent the tyre compound used in each stint for each driver, and different columns such as time, pitouttime, tyrelife and many others are also shown.

 

 

Task 9

 

Figure 14: Visualization of the number of laps in each stint for each driver

 

Task 9 is based on the visualization of the number of laps in each stint for each driver, and also it shows different columns such as stint 1, stint 2, and others.

 

 

 

 

Task 10

 

Figure 15: Visualization of the number of laps and tyre compound used in each stint for each driver

 

Task 10 represents the visualization of the number of laps and tyre compound used in each stint for each driver.

 

 

 

 

 

Figure 16: Output for the number of laps and tyre compound used in each stint for each driver

The above figure is the output visualization to show the number of laps and tyre compound used in each stint for each driver

 

 

 

 

Task 11

 

 

Figure 17: Coding visualization for the median lap time tends to decrease with lap number

 

The above figure is the coding visualization to complete task 11, for the median lap time tends to decrease with lap number.

 

 

 

Figure 18: Plot for the median lap time tends to decrease with lap number

Therefore, the above figure represents the graph plotting for he median lap time tends to decrease with lap number.

 

Task 12

 

 

 

 

Figure 19: Coding visualization of the line of best fit

Task 12 is based on the plot representation of the line of best fit and the above figure is the coding visualization of that same.

Figure 20: Plot visualization for the line of best fit vs. lap number

It is the plot visualization for the line of best fit vs. lap number, in that case blue color shows the data and the red line represents the line of Best fit.

Task 13

 

 

Figure 21: Coding visualization to compute the fuel-corrected lap time for each lap

It is the coding visualization for task 13, which means it represents the computation of fuel-corrected lap time for each lap.

 

 

Figure 22: Line plot visualization to compute the fuel-corrected lap time for each lap

The above figure is a graphical visualization, which represents to computes the fuel-corrected lap time for each lap.

Task 14

 

 

Figure 23: Coding visualization of the implementation of soft compound tyres

 

 

It is the coding visualization for task 14, which means it represents the implementation of soft compound tyres.

Figure 24: Graph for fuel-corrected lap time vs. tyre age

The above figure is a graphical visualization, which represents a Graph for fuel-corrected lap time vs. tyre age (Shen et al. 2022).

 

Task 15

 

 

Figure 25: Coding to smooth the noise from the curve

 

 

It is the coding visualization for task 15, which means it represents the implementation of smoothing the noise from the curve.

 

Figure 26: Plot for the rolling average

The above figure is a graphical visualization, which represents a Graph of the rolling average.

 

 

 

 

 

 

Task 16

 

 

 

Figure 27: Coding visualization to plot a curve for soft median and hard tyre compounds

 

It is the coding visualization for task 16, which means it represents a Coding, that can used to plot a curve for soft median and hard tyre compounds.

 

 

 

Figure 28: Plot visualization to display three tyes of tyre compound together.

The above figure is a graphical visualization, which represents a Graph to display three tyes of tyre compounds together.

Reference List

Shen, L., Shen, E., Luo, Y., Yang, X., Hu, X., Zhang, X., Tai, Z. and Wang, J., 2022. Towards natural language interfaces for data visualization: A survey. IEEE transactions on visualization and computer graphics.

Sievert, C., 2020. Interactive web-based data visualization with R, Plotly, and Shiny. CRC Press.

Waskom, M.L., 2021. Seaborn: Statistical data visualization. Journal of Open Source Software, 6(60), p.3021.

Yang, Y., 2022. Spatial analytics and data visualization. Handbook of e-Tourism, pp.595-616.